I. Field of the Invention
The present invention relates to methods for profiling, engineering, manufacturing and classifying various types of tissue. More particularly, the present invention relates to the development and use of a novel tissue information database for engineering, manufacturing and classifying various types of tissue. The novel database includes structural, cell function and/or mechanical indices that correspond to statistically significant representations of tissue characteristics associated with various tissue populations.
II. Description of the Related Art
Currently a clear understanding exists of the gross anatomy of the human body (i.e., structural information at the macroscopic level.) Sequencing of human genome has provided information at the genetic level (molecular and submicroscopic.) However, little if any reliable structural information exists at the tissue level (1-1000 microns, i.e., microscopic to mesoscopic.) It is believed that if reliable, multi-dimensional tissue structural information existed, such information would serve to enhance and accelerate new advances in tissue engineering, drug design, gene discovery and genomics research.
Tissue engineering is an emerging segment within the biotechnology industry. Currently, an approach known as xe2x80x9crandomxe2x80x9d tissue engineering is used for making simple two-dimensional tissues that do not require a blood supply, e.g., skin and cartilage. In the random tissue engineering approach, cells are placed in suspension on culture plates or within sponge-like polymer matrices and the respective tissues are grown in incubators with minimal intervention. While structurally simple tissues may be manufactured today in this manner, there is general agreement that this approach will not work for more complex tissues such as muscle and vascularized organs, and that these applications will require more complex growth environments whose applications will depend on tissue knowledge. Rather than using random tissue engineering. Applicants believe that a new methodology referred to as xe2x80x9crationalxe2x80x9d tissue engineering will be required to make more complex tissues such as muscle and vascularized organs. Applicants believe that rational tissue engineering will use structural information at the tissue level, as well as mechanical and cell function information on tissue, in order to develop complex three-dimensional xe2x80x9cblueprintsxe2x80x9d of tissue. These blueprints will then be used to manufacture complex tissue on a microscopic level by delivering the proper cells and intercellular constituents required for generation of the tissue during the manufacturing process.
In order for the rational tissue engineering approach discussed above to be successful, structural information at the tissue level, as well as mechanical and cell function information on tissue, will be required and such information must be made accessible to persons in the tissue engineering, drug design and genomics research fields. It is an object of the present invention to develop such tissue information and to provide this information to persons and entities in the tissue engineering/manufacturing, drug design and genomics research fields. It is a further object of the present invention to use this tissue information to evaluate, classify and/or perform quality control on living and manufactured tissue specimens provided by tissue suppliers. With respect to manufactured tissue specimens, it is a particular object of the present invention to use the tissue information that is the subject of the present invention to identify normal elements of such manufactured tissue specimens in cases where, for example, such manufactured tissue specimens do not appear normal in total but contain elements that appear and/or function normally.
These and other objects will become apparent from the description which follows.
The present invention is directed to an online database that includes indices representative of a tissue population. In the method of the present invention, a sample of normal tissue specimens obtained from a subset of a population of subjects with shared characteristics are profiled in order to generate a plurality of structural indices that correspond to statistically significant representations of characteristics of tissue associated with the population. The structural indices include cell density, matrix density, blood vessel density and layer thickness.
In one embodiment, the tissue specimens obtained from the subset of the population are profiled by imaging a plurality of sections of each tissue specimen from the subset. Distributions of cell density values, matrix density values and blood vessel density values associated with the plurality of sections are then determined in accordance with the results of the imaging. A cell density index representative of tissue associated with the population is determined in accordance with the distribution of cell density values, a matrix density index representative of tissue associated with the population is determined in accordance with the distribution of matrix density values, and a blood vessel density index representative of tissue associated with the population is determined in accordance with the distribution of blood vessel density values. In one example, the cell density index is determined by calculating a statistical average of the distribution of cell density values, the matrix density index is determined by calculating a statistical average of the distribution of matrix density values, and the blood vessel density index is determined by calculating a statistical average of the distribution of blood vessel density values. Each statistical average of a distribution values represents, for example, a mean, median or mode of the distribution of values.
In accordance with a further aspect, the structural indices include a further cell density index corresponding to an index of dispersion of the distribution of cell density values, a further matrix density index corresponding to an index of dispersion of the distribution of matrix density values, and a further blood vessel density index corresponding to an index of dispersion of the distribution of blood vessel density values. Each index of dispersion of a distribution values represents, for example, a standard deviation, standard error of the mean or range of the distribution of values.
In accordance with a still further aspect, distributions of relative cell location values, relative matrix location values and relative blood vessel location values associated with the plurality of sections are also determined in accordance with the results of the imaging. A relative cell location index representative of tissue associated with the population is determined in accordance with the distribution of relative cell location values, a relative matrix location index representative of tissue associated with the population is determined in accordance with the distribution of relative matrix location values, and a relative blood vessel location index representative of tissue associated with the population is determined in accordance with the distribution of relative blood vessel location values. In one example, the relative cell location index is determined by calculating a statistical average of the distribution of relative cell location values, the relative matrix location index is determined by calculating a statistical average of the distribution of relative matrix location values, and the relative blood vessel location index is determined by calculating a statistical average of the distribution of relative blood vessel location values.
In accordance with yet a further aspect, the structural indices include a further relative cell location index corresponding to an index of dispersion of the distribution of relative cell location values, a further relative matrix location index corresponding to an index of dispersion of the distribution of relative matrix location values, and a further relative blood vessel location index corresponding to an index of dispersion of the distribution of relative blood vessel location values. Again, each index of dispersion of a distribution values represents, for example, a standard deviation, standard error of the mean or range of the distribution of values.
Various imaging modalities may be used for profiling the tissue specimens and generating the structural indices described above. For example, light microscopy, fluorescent microscopy, spectral microscopy, hyper-spectral microscopy, electron microscopy, confocal microscopy and optical coherence tomography may be used for profiling the tissue specimens in accordance with the present invention. A combination of such imaging modalities can also be used for profiling tissue specimens in accordance with the present invention.
In addition to structural indices described above, one or more mechanical indices may be determined from the normal tissue specimens. In accordance with this aspect of the invention, the sample of normal tissue specimens obtained from the subset of the population with shared characteristics is further profiled in order to generate one or more mechanical indices that correspond to statistically significant representations of characteristics of tissue associated with the population. One of the mechanical indices may correspond to a modulus of elasticity associated with the normal tissue specimens. The mechanical index corresponding to the modulus of elasticity is preferably determined by obtaining a distribution of elasticity values associated with the plurality of sections discussed above, and then determining an elasticity index representative of tissue associated with the population in accordance with the distribution of elasticity values. The elasticity index preferably represents the statistical average (e.g., mean, median or mode) of the distribution of elasticity values. In accordance with a further aspect, a further elasticity index representative of the index of dispersion of the distribution of elasticity values is determined. This further elasticity index preferably represents the standard deviation, standard error of the mean or range of the distribution of elasticity values.
A further mechanical index corresponding to the mechanical strength (e.g., breaking or tensile strength) associated with the normal tissue specimens may also be determined. The mechanical index corresponding to the breaking strength is preferably determined by obtaining a distribution of breaking strength values associated with the plurality of sections discussed above, and then determining a breaking strength index representative of tissue associated with the population in accordance with the distribution of breaking strength values. The breaking strength index preferably represents the statistical average (e.g., mean, median or mode) of the distribution of breaking strength values. In accordance with a further aspect, a further breaking strength index representative of the index of dispersion of the distribution of breaking strength values is determined. This further breaking strength index preferably represents the standard deviation, standard error of the mean or range of the distribution of breaking strength values.
In addition to structural and mechanical indices, one or more cell function indices may be determined from the normal tissue specimens. In accordance with this aspect of the invention, a plurality of cell function assays are performed on the sample of normal tissue specimens from the subset of the population of subjects with shared characteristics. The results of the cell function assays are used to generate a plurality of cell function indices that correspond to statistically significant representations of characteristics of tissue associated with the population. The cell function indices are optionally used to form a cell function map that is stored in a tissue information database. In an alternate embodiment, only the cell function indices and/or the cell function map (and not the structural or mechanical indices) are determined. The cell function indices used in connection with this aspect of the invention correspond, for example, to (i) location, type and amount of DNA in the normal tissue specimens from the subset, (ii) location, type and amount of mRNA in the normal tissue specimens from the subset, (iii) location, type and amount of cellular proteins in the normal tissue specimens from the subset, (iv) location, type and amount of cellular lipids in the normal tissue specimens from the subset, and/or (v) location, type and amount of cellular ion distributions in the normal tissue specimens from the subset.
In accordance with further aspects of the invention, the correlation between various one of the indices described above may also be determined. For example, a correlation between two structural indices, a correlation between two mechanical indices, a correlation between two cell function indices, a correlation between a structural index and a mechanical index, a correlation between a structural index and a cell function index, and/or a correlation between a mechanical index and a cell function index may also be determined.
The normal tissue specimens profiled to generate the structural, mechanical and/or cell function indices described above correspond, for example, to a set of either normal intestine tissue specimens, normal cartilage tissue specimens, normal eye tissue specimens, normal bone tissue specimens, normal fat tissue specimens, normal muscle tissue specimens, normal kidney tissue specimens, normal brain tissue specimens, normal heart tissue specimens, normal liver tissue specimens, normal skin tissue specimens, normal pleura tissue specimens, normal peritoneum tissue specimens, normal pericardium tissue specimens, normal dura-mater tissue specimens, normal oral-nasal mucus membrane tissue specimens, normal pancreas tissue specimens, normal spleen tissue specimens, normal gall bladder tissue specimens, normal blood vessel tissue specimens, normal bladder tissue specimens, normal uterus tissue specimens, normal ovarian tissue specimens, normal urethra tissue specimens, normal penile tissue specimens, normal vaginal tissue specimens, normal esophagus tissue specimens, normal anus tissue specimens, normal adrenal gland tissue specimens, normal ligament tissue specimens, normal intervertebral disk tissue specimens, normal bursa tissue specimens, normal meniscus tissue specimens, normal fascia tissue specimens, normal bone marrow tissue specimens, normal tendon tissue specimens, normal pulley tissue specimens, normal tendon sheath tissue specimens, normal lymph node tissue specimens, or normal nerve tissue specimens. In further embodiments, the tissue specimens profiled correspond to plant or animal tissue types, composite tissue types, virtual tissue types or food tissue types.
In accordance with a further aspect, the present invention is directed to a computer implemented method for providing information representative of a plurality of tissue types to a subscriber. Tissue information representative of a plurality of tissue types (e.g., the structural, mechanical and/or cell function indices described above for a plurality of tissue types and the correlation results described above for a plurality of tissue types) is stored in a database. For each tissue type, the database includes, for example, a plurality of structural indices generated from a sample of normal tissue specimens obtained from a subset of a population of subjects with shared characteristics. The structural indices correspond to statistically significant representations of characteristics of tissue associated with the population. The plurality of structural indices include cell density, matrix density, blood vessel density and layer thickness. For each tissue type, the database alternatively includes a plurality of the cell function and/or mechanical indices described above either alone, or in combination with the aforementioned structural indices. Subscribers or users interested in engineering, classifying, manufacturing or analyzing tissue are provided access to the database in exchange for a subscription fee. The subscribers may optionally measure parameters associated with subscriber-supplied tissue samples. The subscriber-supplied tissue samples are then classified by comparing measured parameters associated with the subscriber-supplied tissue samples with the tissue information stored in the database (e.g., the structural, mechanical and/or cell function indices described above and/or the correlation results described above.) In addition to the other tissue types described above, the database optionally stores indices representative of one or more abnormal tissue types, and the subscriber-supplied tissue samples are classified as either normal or abnormal by comparing measured parameters associated with the subscriber-supplied tissue samples to the tissue information stored in the database. Where the subscriber-supplied tissue specimens correspond to manufactured tissue specimens, measured parameters associated with the subscriber-supplied tissue samples may be compared to the tissue information stored in the database in order to identify normal elements of such manufactured tissue specimens in cases where, for example, such manufactured tissue specimens do not appear normal in total but contain elements that appear and/or function normally.